Handwriting recognition programs generally operate by comparing data generated from handwritten words or characters to stored recognition data in an attempt to correctly replicate the handwritten words or characters as typewritten text. Occasionally, the recognition process generates errors in the typewritten representation of the handwritten characters due to poor handwriting or deficiencies in the computer programs that attempt to recognize the handwritten characters. Accordingly, advanced handwriting recognition programs include weighting values associated with some or all of the stored recognition data that are used in the recognition process to improve the likelihood of correctly recognizing the handwritten input.
Advanced handwriting recognition programs have also experimented with gradually varying the weighting values associated with the stored recognition data responsive to the handwritten input as it is received and processed over time. In this way, the likelihood of correct recognition of handwritten input is further enhanced without so drastically altering the weighting values as to tailor the stored handwriting recognition data to a single individual.
However, known methods for adapting the weighting values of stored recognition data may actually reduce the accuracy of the handwriting recognition process since weight variations based upon handwritten input will cause the weighting values to be changed in response to user errors in the handwritten words and characters. The likelihood of impairing recognition accuracy in this manner is particularly acute if handwriting errors are not promptly corrected by the user. For this reason, prior adaptive weighting handwriting recognition techniques were designed to vary the weighting values of the stored character recognition data very gradually so as not to reduce recognition accuracy beyond the point of the potential benefits of adapting the recognition weighting values at all. The result of this practice, however, was to substantially extend the time before a user could appreciate the benefits of enhanced recognition accuracy via adapting the recognition weighting values.
Accordingly, to fully realize the benefits of an adaptive weighting handwriting recognition system, a weight variation process is needed that quickly improves recognition accuracy while minimizing the detrimental potential of reduced recognition accuracy known in prior attempts to provide adaptive handwriting recognition.